System and method for validating broadband service recommendation

ABSTRACT

Described are an apparatus, system, and method for method for validating a broadband service for recommendation. The method comprises: collecting data associated with the broadband service; evaluating the collected data for service recommendations, the service recommendations including upgrades and downgrades to the broadband service; and validating broadband service recommendations, in response to evaluating the collected data, before presenting the broadband service recommendations to user of the broadband service.

CLAIM FOR PRIORITY

This application claims priority to PCT Patent Application Serial No.PCT/US13/62691, filed on 30 Sep. 2013, titled “SYSTEM AND METHOD FORVALIDATING BROADBAND SERVICE RECOMMENDATION,” and which is incorporatedby reference in entirety.

BACKGROUND

In current practice, Wide Area Network (WAN) and/or Local Area Network(LAN) performance information is not centrally analyzed by acommunication device coupled to such networks to account for informationsuch as topological information, geographical information, user'snetwork usage pattern, quality of network connection, time, throughput,user behavior, usage data, etc. Accordingly, user behavior associatedwith user's broadband service may not be contextually analyzed by anycentral system to provide service recommendation to the user of thebroadband service according to its broadband service usage. Furthermore,a lack of validated service recommendation may result negatively interms of customer (user) satisfaction of the broadband service.

Lack of validated service recommendation may also result in thecommunication devices (e.g., a smart phone, computer, a router, DigitalSubscriber Line, etc.) to adapt a service that may not be compatiblewith the communication device and/or service plan. Typically, operatorsrely on basic information such as loop lengths to determine the serviceproducts of customers, which often leads to incorrect service upgradesor downgrades. Such process is inefficient in terms of resources andcosts as customers are more likely to call and complain, and callcenter/technicians should handle their complaints by manually adjustingservices, or physically fixing the broadband service hardware (e.g.,Digital Subscriber Line (DSL) lines).

BRIEF DESCRIPTION OF THE DRAWINGS

Embodiments of the disclosure will be understood more fully from thedetailed description given below and from the accompanying drawings ofvarious embodiments of the disclosure, which, however, should not betaken to limit the disclosure to the specific embodiments, but are forexplanation and understanding only.

FIG. 1 is a communication network with some or all communication deviceshaving a downloadable agent and/or machine executable instructions tovalidate broadband services for recommendation, according to oneembodiment of the disclosure.

FIG. 2A is a high level method for service recommendation includingvalidating service recommendations, according to one embodiment of thedisclosure.

FIG. 2B is a high level method for service recommendation includingvalidating service recommendations, according to another embodiment ofthe disclosure.

FIG. 3 is a method of validating service recommendations, according toone embodiment of the disclosure.

FIG. 4 is a system for validating service recommendations, according toone embodiment of the disclosure.

FIG. 5 is a processor-based system having machine-readable storagemedium with computer executable instructions to validate servicerecommendations, according to one embodiment of the disclosure.

DETAILED DESCRIPTION

The embodiments relate to a system and method for qualifying a broadbandservice (e.g., Digital Subscriber Line (DSL) loop) and validatingservices. The embodiments describe a Service Recommender (SR) thatrecommends service upgrade or downgrade using current and historicalbroadband service conditions. SRs use various state-of-the-artestimation algorithms, but may suffer from recommending false positivesand negatives due to estimation errors and time variations.

In one embodiment, when service providers use SRs, they may identifycustomers for upgrades, and call them for up-sell (i.e., upgradebroadband service from the current service deal), or identify customersfor downgrades if it identifies an over-sell (e.g., curtail some of thefeatures of the broadband service to improve overall experience of thebroadband service by a user). Once agreement is reached between users ofthe broadband service and its provider(s), service providers mayactually change service products and profiles of the broadband servicefor the user. After service and profile changes, if the broadbandservice does not meet the service requirement, service providers maychange services, or dispatch technicians to fix the broadband service.In one embodiment, to reduce impacts of false positives of servicerecommendations (which may be quite costly), the embodiments of SRsvalidate its recommendations by trying out the new services temporarilyand evaluating the performance of the broadband service in a fullyautomatic manner.

In one embodiment, SR process comprises the process of data collection,evaluation of broadband service based on the collected data, andvalidation of broadband service recommendations including upgrades anddowngrades to the broadband service before presenting the broadbandservice recommendations to the user of the broadband service.

The term “performance” generally refers to network throughput (e.g.,TCP/UDP), latency, jitter, connectivity, error rates, power consumption,transmit power, etc. Improving performance of the communication systemincludes increasing throughput, reducing error rate and latency,improving (i.e., reducing) jitter, reducing power consumption, etc. forthe communicating system.

In one embodiment, SR validation process comprises checking eligibilityof broadband service (e.g., of DSL lines) for SR validation. In oneembodiment, broadband service product currently in use by the user isupdated temporarily (e.g., for a few hours or a day). In one embodiment,profile optimization process is performed on the updated broadbandservice. In such an embodiment, a default profile for the DSL line isprovided after a service product change may not work or may notstabilize the DSL line at issue.

DSL profiles are complex and include many factors that constantlyinteract, such as power levels and margins, bit rates, interleaving, andforward error correction schemes. Operators have traditionally defined alimited number of profiles for their network and applied them to theirDSLs manually using simple heuristics such as loop length. Each loop inthe network is different, however, and often the result of thetraditional process is that lines are either under-provisioned by beingprogrammed to a speed lower than what they can support, orover-provisioned by being programmed to a speed that is too high tomaintain stability. Under-provisioned lines lead to lost revenueopportunities for higher-speed services or for applications such asIPTV. Over-provisioned lines lead to higher maintenance costs fromcustomer complaints and high churn rates.

Based on the DSL operator's service tiers and quality-of-servicetargets, in one embodiment, the profile optimization automaticallyconfigures all lines in the network to the highest possible stablespeed. In one embodiment, the profile optimization is run proactively onall lines in an operator's network periodically, often on a daily basis.In one embodiment, the profile optimization can also be run reactivelyin the case of newly provisioned lines, or at the request of technicalor customer support personnel.

For example, DSL lines which are now operating on the updated broadbandservice product are evaluated to determine their performance with theupdated product. In one embodiment, data is collected and results fromprofile optimization process are evaluated and different serviceproducts are tried for the user to determine an optimum performingbroadband service product under the circumstances (e.g., location,physical line limits, maximum throughput, etc). In one embodiment, afterevaluation of the collected data, original broadband service productsettings are restored for the user, and the user is provided with arecommendation about improving its current broadband service. Onetechnical effect of the embodiments is that the user is provided with avalidated broadband service recommendation. Accordingly, offers ofservices which are not sustainable are avoided.

The term “TCP” stands for Transmission Control Protocol. The term “UDP”refers to User Datagram Protocol. The term “successful” generally refersto an indication suggesting safe receipt of a packet that is oftenconfirmed by ACK (acknowledge) message packet. In another embodiment,operational data such as error counts, retransmission counts,modulation, signal strength, etc. are used to estimate the performanceand throughput of the communications link.

The term “Local Area Network” (LAN) generally refers to a computer orcommunication network that interconnects computers or communicationdevices in a limited area such as a home, school, computer laboratory,or office building using network media.

The term “Wide Area Network” (WAN) generally refers to atelecommunication network that covers a broad area (i.e., any networkthat links across metropolitan, regional, or national boundaries)compared to the limited area covered be a LAN.

In the following description, numerous details are discussed to providea more thorough explanation of embodiments of the present disclosure. Itwill be apparent, however, to one skilled in the art, that embodimentsof the present disclosure may be practiced without these specificdetails. In other instances, well-known structures and devices are shownin block diagram form, rather than in detail, in order to avoidobscuring embodiments of the present disclosure.

Note that in the corresponding drawings of the embodiments, signals arerepresented with lines. Some lines may be thicker, to indicate moreconstituent signal paths, and/or have arrows at one or more ends, toindicate primary information flow direction. Such indications are notintended to be limiting. Rather, the lines are used in connection withone or more exemplary embodiments to facilitate easier understanding ofa circuit or a logical unit. Any represented signal, as dictated bydesign needs or preferences, may actually comprise one or more signalsthat may travel in either direction and may be implemented with anysuitable type of signal scheme.

In the following description and claims, the term “coupled” and itsderivatives may be used. The term “coupled” generally refers to two ormore elements which are in direct contact (physically, electrically,magnetically, electromagnetically, optically, etc.). The term “coupled”generally may also refer to two or more elements that are not in directcontact with each other, but still cooperate or interact with eachother.

Unless otherwise specified, the use of the ordinal adjectives “first,”“second,” and “third,” etc., to describe a common object, merelyindicate that different instances of like objects are being referred to,and are not intended to imply that the objects so described must be in agiven sequence, either temporally, spatially, in ranking or in any othermanner.

FIG. 1 is a communication network 100 with some or all communicationdevices having a downloadable agent (DA) and/or machine executableinstructions to validate broadband services for recommendation,according to one embodiment of the disclosure.

In one embodiment, communication network 100 comprises a local network101 (e.g., a network at home) having Customer Premises Equipment (CPE)101 a and a personal computer (PC) 101 b. In one embodiment, LAN 101optionally comprises a line enhancement device 101 c which is any devicecoupled to DSL 110 that improves the quality or performance on DSL 110.In one embodiment, line enhancement device 101 c is a standalone device.In another embodiment, line enhancement device 101 c is integrated withCPE 101 a. In one embodiment, one or more devices of LAN (e.g., homeLAN) 101 are operable to communicate with server 105 via Internet 109(via wired or wireless connections).

In one embodiment, communication network 100 comprises a server 105coupled to a database 106. In one embodiment, server 105 and/or thedatabase 106 reside in a cloud 104.

The term “cloud” refers generally to cloud computing which is thedelivery of computing and storage capacity as a service to a communityof end-recipients. The term “cloud” is indicated with use of acloud-shaped symbol 104 as an abstraction for the complex infrastructureit contains in system diagrams. Cloud computing entrusts services with auser's data, software and computation over a network. In one embodiment,server 105 resides in cloud 104 and is operable to perform complexanalysis (e.g., statistical) based on information collected from othercommunication devices via the Internet.

In one embodiment, communication network 100 comprises DSL accessequipment 103 a (also called a DSL access network, or DSL node) which isoperable to communicate with CPE 101 a via DSL line 110. In oneembodiment, DSL access equipment 103 a comprises a DSLAM (digitalsubscriber line access multiplexer). In one embodiment, DSL accessequipment 103 a comprises a CO (central office). In one embodiment, DSLaccess equipment 103 a receives control signals 108 from server 105 thatinstruct a DSL operator 103 b about ways to improve performance of itscustomers e.g., CPE 101 a, etc.

In one embodiment, control signals 108 include at least one or more ofsignals or commands related to: power, (e.g., transmit power); spectrumcontrol, (e.g., Power Spectral Density (PSD) mask, margin, data rate,latency/delay); coding, (e.g., Forward Error Correction (FEC) coding).

In one embodiment, cloud 104 communicates with DSL access equipment 103a via Network Management System (NMS) 103 c. The NMS 103 c mayrepresents any management system used by the DSL network operators orDSL service providers to manage the DSL lines and their network. In oneembodiment, operational data can be collected from NMS 103 c of theservice provider. In one embodiment, NMS 103 c is communicativelycoupled to DSL modem pairs. In one embodiment, operational andperformance data is collected from NMS 103 c. In one embodiment, a DSLline can be controlled by NMS 103 c. In one embodiment, control signals108 are received by NMS 103 c.

In one embodiment, server 105 is operable to access externalcommunication devices (external to cloud 104) through cloud-basedapplications via a web browser or mobile application. In theembodiments, DA 102 is operable to communicate with resources (e.g.,server 105, database 106) of cloud 104. In one embodiment, DA 102 may bedownloaded from any platform e.g., a disk, memory stick, web browser,web server, etc. In one embodiment, DA 102 associated with acommunication device executes on an Internet browser (e.g., Safari®,Netscape®, FireFox®, Internet Explorer®, etc.). In one embodiment, DA102 associated with the communication device is accessible remotely viathe Internet.

In one embodiment, DA 102 is operable to execute on multiple computingplatforms with different operating systems. For example, DA 102 mayoperate on operating systems including Android, Berkley SoftwareDistribution (BSD), iOS, GNU/Linux, Apple Mac OS X, Microsoft Windows,Windows Phone, and IBM z/OS. In one embodiment, DA 102 is operable toexecute in a virtual machine (VM). A VM is a software implementation ofa machine (e.g., a computer) that executes programs like a physicalmachine. Examples of virtual machines include a Java Virtual Machine andthe previously mentioned operating systems executing in VMWare, VirtualBox or the like. In one embodiment, DA 102 may receive automatic updatesto keep the application up to date with the latest features. In oneembodiment, the downloadable agent is dynamically downloaded to thecomputing device.

The term “dynamically” generally refers to automatic action. The term“dynamically” also refers to downloading of an agent by a computingdevice on-demand and prior to use of an agent. A dynamically downloadedagent may be deleted from the computing device following the use of thatagent. The term “dynamically” may also refer to automatic (i.e., withlittle or no human interaction) adjusting of service profile of abroadband subscriber with a new service profile.

In one embodiment, communication network 100 comprises a wirelessdevice, for example, a smart device 107 (e.g., smart phone, tablet,etc.) with a DA 102. In one embodiment, DA 102 is operable to review ananalysis report generated by server 105 for any of the communicatingdevices it has authorization to access.

In one embodiment, server 105 is operable to receive WAN performanceinformation from a DA 102. In one embodiment, DA 102 is executable on acomputing device (e.g., 101 a-b, 107, 113) coupled to LAN 111 of abroadband subscriber. In one embodiment, LAN 111 is coupled by anotherdevice to WAN 112. In one embodiment, a DSL modem and a home gatewaycouple LAN 111 to WAN 112. In one embodiment, the DSL modem and homegateway are integrated into a single enclosure.

In one embodiment, DA 102 associated with the communication devicecollects data locally within the communication device and thenperiodically sends the collected data to server 105. In one embodiment,DA 102 may wait for certain conditions or thresholds to be met beforesending all collected data to server 105.

In one embodiment, conditions and/or thresholds are related to afunction of the type of data collected. For example, collected data mayinclude at least one of: topological information, geographicalinformation, time, throughput, latency, jitter, packet loss, type ofcommunication device, device network identification, manufacturer andmodel of equipment, equipment characteristics, firmware, user's networkusage pattern, RF characteristics including at least one of: signalpower, frequency bands and mode of operation, environment statistics, ordata on operation of communication devices.

In one embodiment, conditions are limits or thresholds on a performancelevel related to collected data. In one embodiment, a condition is anupper limit on jitter, or a lower limit on throughput. For example, ifthroughput drops below a lower limit/threshold, then DA 102 may reportand send the data to server 105. In another example, if packet lossexceeds an upper limit, then DA 102 may report and send the data to theserver. In one embodiment, a condition is time expiration on a scheduledcollection. For example, DA 102 may send data to server 105 after apre-defined time is expired.

In another embodiment, server 105 collects information from the DA's,through server initiated communication. In one embodiment, server 105collects information by polling on scheduled basis. One such example ofpolling is ping. In one embodiment, server 105 may send a signal to a DA102, or ping a DA 102, or communicate with a DA 102 on scheduled basis,after which DA 102 sends collected information to server 105.

In one embodiment, the computing device is one of: computer, personalcomputer, laptop/desktop, smart phone, tablet computing device; anaccess point (AP); a base station; a wireless smart phone device; awireless LAN device; an access gateway; a router, a performanceenhancement device; a DSL CPE modem; a cable CPE modem; an in-homepowerline device; a Home Phoneline Network Alliance (HPNA) based device;an in-home coax distribution device; a G.hn (Global Home NetworkingStandard) compatible device; an in-home metering communication device;an in-home appliance communicatively interfaced with the LAN; a wirelessfemtocell base station; a wireless Wi-Fi compatible base station; awireless mobile device repeater; a wireless mobile device base station;nodes within an ad-hoc/mesh network; a set-top box (STB)/set-top unit(STU) customer electronics device; an Internet Protocol (IP) enabledtelevision; an IP enabled media player; an IP enabled gaming console; anEthernet gateway; a computing device connected to the LAN; an Ethernetconnected computer peripheral device; an Ethernet connected router; anEthernet connected wireless bridge; an Ethernet connected networkbridge; and an Ethernet connected network switch.

In one embodiment, server 105 is operable to store the WAN performanceinformation in database 106 associated with server 105. In oneembodiment, server 105 is operable to store the WAN performanceinformation with an associated timestamp. In one embodiment, DA 102 isoperable to collect LAN performance data from at least one of thecomputing device (e.g., 101 b) and another device (e.g., PC 113) coupledto LAN 111. In one embodiment, server 105 is operable to receive the LANperformance data from DA 102.

In one embodiment, the WAN and LAN performance information include atleast one of: topological information, geographical information, time,throughput, latency, jitter, packet loss, type of communication device,device network identification, manufacturer and model of equipment,equipment characteristics, firmware, user's network usage pattern, RFcharacteristics including at least one of: signal power, frequency bandsand mode of operation, environment statistics, or data on operation ofcommunication devices.

Topological information may include information regarding the WAN or LANtopology. For example, whether a DSL modem is behind a firewall, orwhether the Internet gateway is connected to a Wi-Fi access point via arouter. The geographical information may include the address or globalpositioning system (GPS) location of the WAN or LAN modem, or theInternet gateway. The geographical information may be useful forexample, for neighborhood analysis, and for correlating informationregarding neighbors, or users in a given geographical location.Environment Statistics may include any statistics related to theenvironment surrounding the WAN or LAN. For example, usage statistics,statistics on periods of peak operation, statistics on the data traffic(peak traffic, average traffic, etc.).

In one embodiment, LAN performance information also includes, withoutlimitation: LAN media type, such as Ethernet, Wi-Fi, or power-lineadapters; LAN media throughput rates; channel assignments for Wi-Fimedia; Wi-Fi mode such as 802.11g or 802.11n; Wi-Fi transmit powerlevels; and spectral masks for power-line communication.

In one embodiment, server 105 is operable to analyze the WAN performanceinformation to generate an analysis result. In one embodiment, server105 is operable to generate analysis result by computing throughput ofDSL connection 110 by collecting current performance metrics associatedwith DSL service. In one embodiment, server 105 is operable to performstatistical analysis, including throughput, based on informationreceived from the DA 102 and other information in the database.

In one embodiment, server 105 is operable to compute throughput of acommunication link (e.g., Wi-Fi or Ethernet link 109) by probing. In oneembodiment, the process of probing comprises: transmitting probing datafrom a communication device (e.g., PC 101 b) to another communicationdevice (e.g., PC 113, PC 114, etc.); and waiting for a predeterminedtime before reading operational data including counter values related touser data traffic. In one embodiment, the counter values include atleast one of packet error counts, packet retransmission counts,successful ACK message counts, etc. The throughput information discussedin this embodiment and other embodiments of this disclosure couldinclude at least one or more of the following: instantaneous speed ordata rate, average data rate, and/or information on the peak and minimumdata rates of a connection or communication link associated with the LANand/or with the associated WAN.

The term “probing” generally refers to testing of a communicationnetwork by sending test pattern/data over the network from onecommunication device to another communication device, and then measuringthe response from the sent test pattern.

The term “operational data” generally refers to user visible oraccessible data and is generally used for debugging and basicperformance monitoring of communication systems.

In one embodiment, the method of probing comprises: transmitting probingdata from a communication device (e.g., PC 101 b) to anothercommunication device (e.g., PC 113); and receiving a report indicatingamount of data or data received by the other communication device.

In one embodiment, server 105 is operable to determine availability ofhigher bandwidth for operating a DSL service. In one embodiment, server105 is operable to determine purchase information (or service productinformation) for improving DSL service performance. In one embodiment,server 105 is operable to determine network, service, or communicationlink utilization information for optimizing a consumer DSL service cost.In one embodiment, server 105 is operable to group data in database 106according to at least one of geographical location, services type,service provider, or time. The service product information includesinformation regarding the type and specification of the DSL service orservices which is a DSL service user/customer has purchased from the DSLservice provider.

In one embodiment, server 105 receives information from other devicesand/or sources other than the communication devices to perform acomprehensive analysis of the performance of the communication system asa whole and/or individually for the communication devices in thecommunication system. Examples of the other devices and/or sourcesinclude near-by radio stations, location of AM radio stations, goals orbusiness rules defined by an operator, weather forecast from theNational Weather Service, etc.

In one embodiment, server 105 is operable to validate the analysis (orevaluated) i.e., service recommendations are validated. In oneembodiment, server 105 is operable to offer availability of higherbandwidth for operating a DSL service to DA 102 of 101 a. In oneembodiment, server 105 is operable to report the analysis result bysending purchase information (or service product information) to PC 101b, smart device 107, or the user for improving DSL service performance.In one embodiment, server 105 is operable to report the analysis resultby sending utilization information to PC 101 b, smart device 107, or anydevice accessible by the user for optimizing consumer DSL service cost.

In one embodiment, DA 102 receives updated or new operational parametersfrom server 105 based on the evaluation performed by server 105. Forexample, server 105 when evaluating the data collected by DA 102 of 101a, also takes into account historical information about thecommunication device 101 a and information from other communicationdevices coupled to the network to determine updated operationalparameters for verification.

In one embodiment, server 105 is operable to report the validatedservice recommendation to at least one of the broadband subscriber andthe broadband subscriber's service provider. In one embodiment, server105 is operable to receive an on-demand change request. In oneembodiment, the on-demand change is associated with at least one of:throughput, latency, packet loss, or jitter. For example, DA 102 of thePC 101 b sends a request via connection 109 to server 105 to acquirehigher throughput than current throughput for its DSL line 110. In suchan embodiment, server 105 performs analysis based on available data indatabase 106 and determines if the on-demand change request by PC 101 bcan be met. In one embodiment, server 105 validates the on-demand changerequest before concluding that the on-demand change request can be met.

In one embodiment, server 105 performs comprehensive analysis torecommend a service profile to a broadband subscriber and the broadbandsubscriber's service provider. In one embodiment, server 105 receivesbroadband data from an agent (e.g., 102 of 115). In one embodiment, theagent is executable on a computing device (e.g., 115) coupled to LAN 111of a broadband subscriber.

In one embodiment, broadband data is user data and at least one of WANperformance information or LAN performance data. In one embodiment, acurrent service profile of the broadband subscriber is identified. Inone embodiment, the received broadband data in view of a current serviceprofile is analyzed by server 105. In one embodiment, a new serviceprofile is determined by server 105 for the broadband subscriberaccording to the analyzed broadband data. In one embodiment, the newservice profile is installed temporarily for the broadband subscriberand the new service profile is then validated.

In one embodiment, cloud 104, server 105, or broadband subscriber'sservice provider dynamically adjusts current service profile of thebroadband subscriber with the new service profile and then validates thenew service profile. In one embodiment, cloud 104 collects dataassociated with the new broadband service profile. In one embodiment,cloud 104 evaluates the collected data for validating the servicerecommendation, the service recommendations including upgrades anddowngrades to the broadband service. In one embodiment, cloud 104validates broadband service recommendations, in response to evaluatingthe collected data, before formally presenting the broadband servicerecommendations to user of the broadband service.

FIG. 2A is a high level method 200 for service recommendation includingvalidating service recommendations, according to one embodiment of thedisclosure. It is pointed out that those elements of FIG. 2A having thesame reference numbers (or names) as the elements of any other figurecan operate or function in any manner similar to that described, but arenot limited to such.

Although the blocks in the flowcharts with reference to FIG. 2A areshown in a particular order, the order of the actions can be modified.Thus, the illustrated embodiments can be performed in a different order,and some actions/blocks may be performed in parallel. Some of the blocksand/or operations listed in FIG. 2A are optional in accordance withcertain embodiments. The numbering of the blocks presented is for thesake of clarity and is not intended to prescribe an order of operationsin which the various blocks must occur. Additionally, operations fromthe various flows may be utilized in a variety of combinations. In oneembodiment, the following process may be performed by cloud 104. Inother embodiments, other computing devices may perform the describedmethods.

At block 201, data is collected associated with a broadband service. Inone embodiment, broadband service is a DSL broadband service. In oneembodiment, the process of collecting data associated with the broadbandservice includes collecting DSL or Wi-Fi data by network monitoring ormanagement tools. In one embodiment, cloud server 105 collects DSL orWi-Fi data through NMS 103 c or by DA 102. In one embodiment, if Wi-Fiis not a separate broadband service subscribed by the user becauseanother communication medium (e.g., cable router, DSL router, etc.) iscoupled to the Wi-Fi network, data collected from Wi-Fi can be used topredict appropriate services (i.e., predict service recommendations).

In one embodiment, the process of collecting data associated with thebroadband service includes collecting back-haul capacity data associatedwith the broadband service. In one embodiment, back-haul capacity of DSLnetworks may be provided by operators, or may be collected at the DSLAMlevel. In one embodiment, if a network has a limited back-haul capacity,service upgrades are recommended for lines with higher needs of higherbandwidth, and service downgrades are recommended for lines with lessneed of higher bandwidth.

In one embodiment, collecting the data associated with the broadbandservice is initiated by the user via a web-based tool, for example,CloudCheck. In one embodiment, collecting the data includes collectinguser preference data or usage data associated with the broadbandservice. In one embodiment, usage data includes at least one of:location of the user; location of the broadband service associated withthe user; Layer 3 data; or amount of data packets transmitted andreceived by the user over a broadband link associated with the broadbandservice. In one embodiment, user preference data includes at least oneof: throughput for a broadband link associated with the broadbandservice; stability of line associated with the broadband service; ordelay of the line.

In one embodiment, collected data includes DSL operational data;historical performance counter data, throughput data, SELT (single endedloop testing) data; Wi-Fi performance data; data collected when the useris shopping online using the broadband service; data collected when theuser is browsing the Internet using the broadband service; datacollected when the user is accessing video online using the broadbandservice; data collected when the user is participating in online gamingactivities using the broadband service; data collected when the user isaccessing cloud-based applications using the broadband service; datacollected when the user is participating in a two-way communicationusing the broadband service; neighborhood configuration data; or dataassociated with services and recommendations of neighboring customers.

At block 202, collected data is evaluated for service recommendations,where service recommendations include upgrades and downgrades to thebroadband service. In one embodiment, evaluating the collected datacomprises analyzing the collected data to determine whether a broadbandline associated with the broadband service can be upgraded to a higherlevel of service. Examples of higher level of services include higherdownstream or upstream rates or both, lower latency (i.e., delay),better error corrections, etc.

In one embodiment, evaluating the collected data comprises identifyingwhether the broadband service is capable of being upgraded or has to bedowngraded. For example, a broadband service whose performance can beimproved because it is being under utilized is capable of beingupgraded. Conversely, a broadband service which is not operating as theservice product claims it should, for example, the broadband servicecannot achieve its advertized performance level because of physicallimitations, then it is capable of being downgraded.

In one embodiment, identifying whether the broadband service is capableof being upgraded is performed when it is determined that validationrecords associated with a physical layer indicate that the physicallayer achieves required data transfer rates. In one embodiment,identifying whether the broadband service is capable of being upgradedis performed when a line associated with the broadband service isexpected to be in stable status (e.g., the status indicates low errorsvia CV counts, or less (or non-frequency) re-initializations via REINITcounts).

In one embodiment, identifying whether the broadband service is capableof being upgraded is performed when it is determined that back-haulcapacity is not a limiting factor for service upgrades. In oneembodiment, if back-haul capacity is a limiting factor, lines associatedwith the broadband service can be prioritized according to factorsincluding users' usage pattern of its broadband service.

In one embodiment, identifying whether the broadband service is capableof being upgraded is performed if similar lines associated with thebroadband service in a geographical area (e.g., neighborhood) meet therequirements of the current broadband service, and are also operatingstably. In one embodiment, identifying whether the broadband service iscapable of being upgraded is performed if the current service productfor the broadband service cannot support users' requirements ofbandwidth use, but the broadband service is capable of supporting theusers' requirements if an upgraded service product is used. One way toinfer users' requirements of bandwidth use is to monitor amount of usertraffic through extra data collection. For example, if users use most oftheir allotted bandwidth, it infers that the current service product isnot enough to support users' requirement for bandwidth use. In oneembodiment, identifying whether the broadband service is capable ofbeing upgraded is performed when the user cannot use the broadbandservice in a stable manner. In such an embodiment, a downgrade ofservice product is recommended.

In one embodiment, evaluating the collected data comprises: assigning ascore according to at least one of: determination that a physical layerof the broadband service is stable; determination that a broadband lineis stable using a different service product; determination thatvalidation records associated with the physical layer indicate that thephysical layer achieves target data transfer rates; and determinationthat back-haul capacity is not a limiting factor for service upgrades.In one embodiment, evaluating the collected data comprises comparing thescore to a threshold.

In one embodiment, score is computed for each target service product.For example, if a line is 3M service, and considered target serviceproducts are 10M and 7M, the process will compute scores for both 10Mand 7M services. In one embodiment, scores are determined by summing upindividual scores.

For example, for 10M service, if the 10M service is expected to bestable then score increments by one. Continuing with the example, assumethat the maximum downstream rate of the line is 8M. Because the 10Mservice does not meet its target rate 10M, then score remains unchanged(i.e., zero added to previous score). If back-haul capacity is largeenough then previous score is incremented by one. 10M service isexpected to improve the downstream rate by 5M, so previous score isupdated by 0.5. In this example the total score the 10M services is 2.5.In another example, for 7M service, if the 7M service is expected to bestable then score increments by one. Continuing with this example, ifthe 7M service meets its target rate 7M then previous score isincremented by one. If back-haul capacity is large enough then previousscore is incremented by one. If 7M service is expected to improve thedownstream rate by 4M, then previous score is updated by 0.4. In thisexample, the total score the 7M service is 3.4. If the threshold isequal to 3, then the embodiments will choose 7M as the recommendationbecause its score is over the threshold, and the highest.

At block 203, broadband service recommendations are validated inresponse to evaluating the collected data. In one embodiment, theprocess of validating the broadband service recommendations is performedbefore presenting the broadband service recommendations to user of thebroadband service. In one embodiment, validating the broadband servicerecommendations comprises prioritizing some broadband lines forvalidation relative to a score. The score may indicate the likelihood ofsuccessful upgrade or downgrade.

In one embodiment, the score is based on availability of capacity inback-haul. For example, if a DSLAM can afford more bandwidth than itscurrent bandwidth i.e., DSL lines can be upgraded without downgradingother lines in the same DSLAM, then a score of +1 is assigned for theDSL lines in the DSLAM.

In one embodiment, the score is based on price of service. For example,a higher score is assigned for more expensive services. In oneembodiment, the score is based on lines, associated with the broadbandservice, which lack validation record. For example, if there is novalidation record then a score of zero is assigned. In one embodiment,the score is based on lines, associated with the broadband service, withrecent changes in equipment of service. In one embodiment, score is notcomputed for a line which is being re-validated because of change inequipment. In one embodiment, the score is based on lines, associatedwith the broadband service, that are more likely to request upgradedservice. For example, a user with higher broadband traffic because ofstreaming IPTV is more likely to request upgraded service. In oneembodiment, the score is based on lines, associated with the broadbandservice, that are more likely to have higher up-sell potential. Forexample, if a user is currently using very low service product (e.g.,3M), but the achievable rate is high for that line (e.g., 20M) then a +1score is assigned. In one embodiment, the score is based on lines,associated with the broadband service, with less accurate servicerecommendations due to higher estimation errors, or due to lack of datacollections.

In one embodiment, validating the broadband service recommendationscomprises updating a parameter set associated with the broadbandservice. In one embodiment, updating the parameter set is donetemporarily. In one embodiment, not all lines are eligible for servicerecommendation validation. In one embodiment, validation of servicerecommendations is performed regularly. For example, every monthvalidation of service recommendations is performed. In one embodiment,validation of service recommendations is performed after an event. Forexample, when equipment associated with the broadband service changes,then validation of service recommendations is performed.

In one embodiment, conditions are imposed to limit the scope ofvalidating service recommendations. For example, validation of servicerecommendations may be limited to a predetermined number of lines,and/or minimum requirements for upgrades or downgrades (e.g., at leastrate increase of more than 30%, etc. triggers a validating process).

FIG. 2B is a high level method 220 for service recommendation includingvalidating service recommendations, according to another embodiment ofthe disclosure. It is pointed out that those elements of FIG. 2B havingthe same reference numbers (or names) as the elements of any otherfigure can operate or function in any manner similar to that described,but are not limited to such.

Although the blocks in the flowcharts with reference to FIG. 2B areshown in a particular order, the order of the actions can be modified.Thus, the illustrated embodiments can be performed in a different order,and some actions/blocks may be performed in parallel. Some of the blocksand/or operations listed in FIG. 2B are optional in accordance withcertain embodiments. The numbering of the blocks presented is for thesake of clarity and is not intended to prescribe an order of operationsin which the various blocks must occur. Additionally, operations fromthe various flows may be utilized in a variety of combinations. In oneembodiment, the following process may be performed by cloud 104. Inother embodiments, other computing devices may perform the describedmethods.

At block 221, data associated with broadband service is collected. Thisstep is similar to step 201 of FIG. 2A. At block 222, availability ofnew data is calculated. For example, cloud 104 determines availabilityof capacity in back-haul, price of other available service products thatcan be added to the existing service product, data about recent changesto equipment of service, availability of DSL performance/operationaldata, etc. At block 223, a determination is made about sufficiency ofavailability of new data. If collected data is not sufficient to make adetermination about what types of upgrades or downgrades can berecommended to a user of the broadband service, the process proceedsback to block 221 and more data associated with the broadband service iscollected.

If collected data is sufficient to make a determination about what typesof upgrades or downgrades can be recommended to a user of the broadbandservice, then the process proceeds to block 224. At block 224, broadbandline associated with the broadband service is evaluated for servicerecommendations. This process is similar to the process discussed withreference to block 202 of FIG. 2A. At block 225, service recommendationsare validated as discussed with reference to block 203 of FIG. 2A.

FIG. 3 is a method 300 of validating service recommendations, accordingto one embodiment of the disclosure. It is pointed out that thoseelements of FIG. 3 having the same reference numbers (or names) as theelements of any other figure can operate or function in any mannersimilar to that described, but are not limited to such.

Although the blocks in the flowcharts with reference to FIG. 3 are shownin a particular order, the order of the actions can be modified. Thus,the illustrated embodiments can be performed in a different order, andsome actions/blocks may be performed in parallel. Some of the blocksand/or operations listed in FIG. 3 are optional in accordance withcertain embodiments. The numbering of the blocks presented is for thesake of clarity and is not intended to prescribe an order of operationsin which the various blocks must occur. Additionally, operations fromthe various flows may be utilized in a variety of combinations. In oneembodiment, the following process may be performed by cloud 104. Inother embodiments, other computing devices may perform the describedmethods.

At block 301, determination is made whether the line associated with thebroadband service is available for SR (service recommendation)validation. One reason for performing the process of block 301 isbecause not all the lines are eligible for SR validation. For example,some DSLAMs have a back-haul capacity issue that prevents the line frombeing upgraded to high rate services. For such DSLAMs SR validation maynot be performed. If determination is made that the line is notavailable for SR validation, then process of block 301 is repeated aftera predetermined programmable time (e.g., 1 month). In one embodiment, itmay not be necessary to validate service recommendations too frequentlyunless there are significant changes in the lines, e.g. equipmentchanges, technician dispatches, etc. If determination is made that theline is available for SR validation, then process proceeds to block 302.

At block 302, the service product currently used by the user is updatedtemporarily with a new service product according to evaluated collecteddata (i.e., process performed by block 202 of FIG. 2A). For example, theservice product is updated to have a better bandwidth for use in gamingor IPTV streaming because the collected data when evaluated indicatedthat the user engaged majority of the time in gaming or IPTV streamingprocesses.

At block 303, profile optimization of lines with new service product isperformed. In one embodiment, one or more parameters are adjusted by theprocess of profile optimization. At block 304, data is collected withthe new service product active. This data is used to verify whether thenew service product which is activated temporarily achieves the resultsanticipated by the evaluating phase. For example, line with the newservice product is monitored and configuration of the line is adjustedto fine optimal performance of the line, and also to determine whetherthe line can operate stably in the temporary service. In one embodiment,the line may be monitored for a predetermined duration which issufficient to collect enough data to validate the temporary service. Forexample, the line with the new service product is monitored for certainnumber of days to increase the accuracy of validation before restoringthe line to its original settings.

At block 305, results associated with the profile optimization arechecked. The checking process determines whether new service productwhich is activated temporarily achieves the results anticipated by theevaluating phase. Once results are checked, at block 306, adetermination is made whether the results are satisfactory. If it isdetermined that the results are not satisfactory, then the serviceproduct is updated again with another service product and the process ofblocks 302 to 306 is repeated. If it is determined that the results aresatisfactory, then the process proceeds to block 307. For example, if aline can operate stably while achieving the minimum required rate of theservice, the service product is considered as satisfactory.

At block 307, original service product is restored for the user. In oneembodiment, original setting including service product and line profileis restored for the line. The user is then presented with a broadbandservice recommendation which is based on the verified servicerecommendation. In one embodiment, the validation process is restartedwhen the validation record becomes obsolete. For example, when lineconditions change (e.g., new equipment is introduced to operate theline), or the validation records become old (e.g., older than one year),then validation process 300 is restarted. In one embodiment, validationprocess 300 is performed when the user is not using the line or theusers' usage of the line is minimal. For example, data collectedovertime provides patterns of user usage behavior and so validationprocess 300 is initiated when user is least likely to notice the process(e.g., in the middle of night).

FIG. 4 is a system 400 for validating service recommendations, accordingto one embodiment of the disclosure. It is pointed out that thoseelements of FIG. 4 having the same reference numbers (or names) as theelements of any other figure can operate or function in any mannersimilar to that described, but are not limited to such.

In one embodiment, system 400 comprises a device 401 (e.g., cloud 104)having the server (e.g., 105) coupled to the database (e.g., 106). Inone embodiment, server 105 comprises: a first module 402 (also calledcollecting means) for collecting broadband data from an agent (e.g.,agent 102). In one embodiment, the agent is executable on a computingdevice coupled to a LAN of a broadband subscriber. In one embodiment,broadband data is user usage data and at least one of WAN performanceinformation or LAN performance data. In one embodiment, agent 102 (i.e.,downloadable agent) includes an Application Programming Interface (API).In one embodiment, first module 402 performs the process described withreference to block 201 of FIG. 2A.

Referring back to FIG. 4, in one embodiment, server 105 comprises asecond module 403 (also called evaluating means) which identifies acurrent service profile of the broadband subscriber and evaluates thereceived broadband data in view of the current service profile. In oneembodiment, second module 403 determines a new service profile for thebroadband subscriber according to the analyzed broadband data. In oneembodiment, second module 403 performs the process described withreference to block 202 of FIG. 2A, and blocks 222, 223, and 224 of FIG.2B.

Referring back to FIG. 4, in one embodiment, server 105 comprises athird module 404 (also called validating means) which validates servicerecommendations prior to recommending a new service product to thebroadband subscriber and/or the broadband subscriber's service provider.In one embodiment, third module 404 performs the process described withreference to block 203 of FIG. 2A, and blocks 301-307 of FIG. 3.

Referring back to FIG. 4, in one embodiment, server 105 comprises: amanagement interface 405 for communicating with the DA 102 (any one ofDAs 1-N, where ‘N’ is a positive integer) via the Internet 406 (e.g.,111, 109 of FIG. 1). In one embodiment, server 105 comprises: a userinterface module 407 for providing access to other communication devicesand for displaying information associated with the first 402, second 403and third 404 modules.

FIG. 5 is a processor-based system 500 having machine-readable storagemedium with computer executable instructions to validate servicerecommendations, according to one embodiment of the disclosure. It ispointed out that those elements of FIG. 5 having the same referencenumbers (or names) as the elements of any other figure can operate orfunction in any manner similar to that described, but are not limited tosuch.

In one embodiment, processor-based system 500 comprises a processor(s)501, memory/database 502, network bus 503, machine-readable storagemedium 504, and network interface 505.

In one embodiment, machine-readable storage medium 504 and associatedcomputer executable instructions 504 a may be in any of thecommunication devices and/or servers discussed herein. Thecomputer-machine-readable/executable instructions 504 a are executed byprocessor 501. Elements of embodiments are provided as machine-readablemedium for storing the computer-executable instructions (e.g.,instructions to implement the flowcharts and other processes discussedin the description).

In one embodiment, database 502 is operable to store data used by theinstructions 504 a (also called software code/instructions). In oneembodiment, network interface 505 is operable to communicate with otherdevices. In one embodiment, the components of processor-based system 500communicate with one another via network bus 503.

The machine-readable storage medium 504 may include, but is not limitedto, flash memory, optical disks, hard disk drive (HDD), Solid StateDrive (SSD), CD-Read Only Memory (CD-ROMs), DVD ROMs, RAMs, EPROMs,EEPROMs, magnetic or optical cards, or other type of machine-readablemedia suitable for storing electronic or computer-executableinstructions. For example, embodiments of the disclosure may bedownloaded as a computer program (e.g., BIOS) which may be transferredfrom a remote computer (e.g., a server) to a requesting computer (e.g.,a client) by way of data signals via a communication link (e.g., a modemor network connection).

Program software code/instructions 504 a executed to implementembodiments of the disclosed subject matter may be implemented as partof an operating system or a specific application, component, program,object, module, routine, or other sequence of instructions ororganization of sequences of instructions referred to as “programsoftware code/instructions,” “operating system program softwarecode/instructions,” “application program software code/instructions,” orsimply “software.” The program software code/instructions 504 atypically include one or more instructions stored at various times invarious tangible memory and storage devices in or peripheral to thecomputing device, that, when fetched/read and executed by the computingdevice, as defined herein, cause the computing device to performfunctions, functionalities and operations necessary to perform a method,so as to execute elements involving various aspects of the function,functionalities, and operations of the method(s) forming an aspect ofthe disclosed subject matter.

For the purposes of this disclosure a module is a software, hardware, orfirmware (or combinations thereof) system, process or functionality, orcomponent thereof, that performs or facilitates the processes, features,and/or functions, functionalities and/or operations described herein(with or without human interaction or augmentation) as being performedby the identified module. A module can include sub-modules. Softwarecomponents of a module may be stored on a tangible machine readablemedium (e.g., 504). Modules may be integral to one or more servers, orbe loaded and executed by one or more servers. One or more modules maybe grouped into an engine or an application.

A tangible machine readable medium (e.g., 504) can be used to storeprogram software code/instructions (e.g., 504 a) and data that, whenexecuted by a computing device 500, cause the computing device 500 toperform a method(s) as may be recited in one or more accompanying claimsdirected to the disclosed subject matter. The tangible machine readablemedium may include storage of the executable software programcode/instructions and data in various tangible locations, including forexample ROM, volatile RAM, non-volatile memory and/or cache and/or othertangible memory as referenced in the present application. Portions ofthis program software code/instructions and/or data may be stored in anyone of these storage and memory devices. Further, the program softwarecode/instructions can be obtained from other storage, including, e.g.,through centralized servers or peer to peer networks and the like,including the Internet. Different portions of the software programcode/instructions and data can be obtained at different times and indifferent communication sessions or in a same communication session.

The software program code/instructions and data can be obtained in theirentirety prior to the execution of a respective software program orapplication by the computing device. Alternatively, portions of thesoftware program code/instructions and data can be obtained dynamically,e.g., just in time, when needed for execution. Alternatively, somecombination of these ways of obtaining the software programcode/instructions and data may occur, e.g., for different applications,components, programs, objects, modules, routines or other sequences ofinstructions or organization of sequences of instructions, by way ofexample. Thus, it is not required that the data and instructions be on atangible machine readable medium in entirety at a particular instance oftime.

Examples of tangible computer-readable media include but are not limitedto recordable and non-recordable type media such as volatile andnon-volatile memory devices, read only memory (ROM), random accessmemory (RAM), flash memory devices, floppy and other removable disks,magnetic disk storage media, optical storage media (e.g., Compact DiskRead-Only Memory (CD ROMS), Digital Versatile Disks (DVDs), etc.), amongothers. The software program code/instructions may be temporarily storedin digital tangible communication links while implementing electrical,optical, acoustical or other forms of propagating signals, such ascarrier waves, infrared signals, digital signals, etc. through suchtangible communication links.

In general, a tangible machine readable medium includes any tangiblemechanism that provides (i.e., stores and/or transmits in digital form,e.g., data packets) information in a form accessible by a machine (i.e.,a computing device), which may be included, e.g., in a communicationdevice, a computing device, a network device, a personal digitalassistant, a manufacturing tool, a mobile communication device, whetheror not able to download and run applications and subsidized applicationsfrom the communication network, such as the Internet, e.g., an iPhone®,Blackberry® Droid®, or the like, or any other device including acomputing device. In one embodiment, processor-based system 500 is in aform of or included within a PDA, a cellular phone, a notebook computer,a tablet, a game console, a set top box, an embedded system, a TV, apersonal desktop computer, etc. Alternatively, the traditionalcommunication applications and subsidized application(s) may be used insome embodiments of the disclosed subject matter.

Reference in the specification to “an embodiment,” “one embodiment,”“some embodiments,” or “other embodiments” means that a particularfeature, structure, or characteristic described in connection with theembodiments is included in at least some embodiments, but notnecessarily all embodiments. The various appearances of “an embodiment,”“one embodiment,” or “some embodiments” are not necessarily allreferring to the same embodiments. If the specification states acomponent, feature, structure, or characteristic “may,” “might,” or“could” be included, that particular component, feature, structure, orcharacteristic is not required to be included. If the specification orclaim refers to “a” or “an” element, that does not mean there is onlyone of the elements. If the specification or claims refer to “anadditional” element, that does not preclude there being more than one ofthe additional element.

Furthermore, the particular features, structures, functions, orcharacteristics may be combined in any suitable manner in one or moreembodiments. For example, a first embodiment may be combined with asecond embodiment anywhere the particular features, structures,functions, or characteristics associated with the two embodiments arenot mutually exclusive.

While the disclosure has been described in conjunction with specificembodiments thereof, many alternatives, modifications and variations ofsuch embodiments will be apparent to those of ordinary skill in the artin light of the foregoing description. The embodiments of the disclosureare intended to embrace all such alternatives, modifications, andvariations as to fall within the broad scope of the appended claims.

The following examples pertain to further embodiments. Specifics in theexamples may be used anywhere in one or more embodiments. All optionalfeatures of the apparatus described herein may also be implemented withrespect to a method or process.

For example, in one embodiment, a method for validating a broadbandservice for recommendation is provided. The method comprises: collectingdata associated with the broadband service; evaluating the collecteddata for service recommendations, the service recommendations includingupgrades and downgrades to the broadband service; and validatingbroadband service recommendations, in response to evaluating thecollected data, before presenting the broadband service recommendationsto user of the broadband service.

In one embodiment, the broadband service is a DSL broadband service. Inone embodiment, collecting the data associated with the broadbandservice includes collecting by network monitoring tools DSL or Wi-Fidata. In one embodiment, the DSL or Wi-Fi data includes at least one of:historical performance data; Digital Subscriber Line (DSL) operationaldata; SELT data; throughput data; Wi-Fi performance data; data collectedwhen the user is shopping online using the broadband service; datacollected when the user is browsing the Internet using the broadbandservice; data collected when the user is accessing video online usingthe broadband service; data collected when the user is participating inonline gaming activities using the broadband service; data collectedwhen the user is accessing cloud-based applications using the broadbandservice; data collected when the user is participating in a two-waycommunication using the broadband service; neighborhood configurationdata; or data associated with services and recommendations ofneighboring customers.

In one embodiment, collecting the data associated with the broadbandservice includes collecting back-haul capacity data associated with thebroadband service. In one embodiment, collecting the data associatedwith the broadband service is initiated by the user via a web-basedtool. In one embodiment, collecting the data includes collecting userpreference data or usage data associated with the broadband service. Inone embodiment, usage data includes at least one of: location of theuser; location of the broadband service associated with the user; Layer3 data; or amount of data packets transmitted and received by the userover a broadband link associated with the broadband service.

In one embodiment, user preference data includes at least one of:throughput for a broadband link associated with the broadband service;stability of line associated with the broadband service; and delay ofthe line. In one embodiment, evaluating the collected data comprises:analyzing the collected data to determine whether a broadband lineassociated with the broadband service can be updated to a higher levelof service.

In one embodiment, evaluating the collected data comprises: identifyingwhether the broadband service is capable of being upgraded or has to bedowngraded. In one embodiment, identifying whether the broadband serviceis capable of being upgraded is performed when it is determined thatvalidation records associated with a physical layer indicate that thephysical layer achieves required data transfer rates. In one embodiment,identifying whether the broadband service is capable of being upgradedis performed when it is determined that back-haul capacity is not alimiting factor for service upgrades.

In one embodiment, evaluating the collected data comprises assigning ascore according to at least one of: determination that a physical layerof the broadband service is stable; determination that a broadband lineis stable using a different service product; determination thatvalidation records associated with the physical layer indicate that thephysical layer achieves target data transfer rates; and determinationthat back-haul capacity is not a limiting factor for service upgrades.In one embodiment, the method further comprises comparing the score to athreshold.

In one embodiment, validating the broadband service recommendationscomprises: prioritizing some broadband lines for validation relative toa score. In one embodiment, the score is based on at least one of:availability of capacity in backhaul; price of service; quality ofcustomer service; lines, associated with the broadband service, whichlack validation records; lines, associated with the broadband service,with recent changes in equipment of service; lines, associated with thebroadband service, that are more likely to request upgraded service;lines, associated with the broadband service, that are more likely tohave higher up-sell potential; or lines, associated with the broadbandservice, with less accurate service recommendations.

In one embodiment, validating the broadband service recommendationscomprises updating a parameter set associated with the broadbandservice. In one embodiment, updating the parameter set is donetemporarily. In one embodiment, the method further comprises performingprofile optimization in response to validating the broadband service,wherein profile optimization to adjust one or more parameters in aparameter set associated with the broadband service.

In one embodiment, validating the broadband service recommendationscomprises: evaluating the broadband service in response to updating theservice; collecting data associated with the broadband service inresponse to evaluating; checking results associated with the profileoptimization in response to evaluating the broadband service andcollecting the data; and restoring original broadband service to theuser in response to checking results.

In one embodiment, the method further comprises applying a test profileto a broadband line associated with the broadband service to determine atype of service the broadband line is capable of handling. In oneembodiment, the method further comprises: presenting the broadbandservice recommendations to the user of the broadband service.

In another example, a machine readable storage medium is provided havinginstructions stored thereon that, when executed, causes a machine toperform a method according to the embodiments discussed above.

An abstract is provided that will allow the reader to ascertain thenature and gist of the technical disclosure. The abstract is submittedwith the understanding that it will not be used to limit the scope ormeaning of the claims. The following claims are hereby incorporated intothe detailed description, with each claim standing on its own as aseparate embodiment.

We claim:
 1. A method for validating a broadband service forrecommendation, the method comprising: collecting data associated withthe broadband service; evaluating the collected data for servicerecommendations, the service recommendations including upgrades anddowngrades to the broadband service; and validating broadband servicerecommendations, in response to evaluating the collected data, beforepresenting the broadband service recommendations to user of thebroadband service.
 2. The method of claim 1, wherein the broadbandservice is a DSL broadband service.
 3. The method of claim 1, whereincollecting the data associated with the broadband service includescollecting by network monitoring tools DSL or Wi-Fi data.
 4. The methodof claim 3, wherein the DSL or Wi-Fi data includes at least one of:historical performance data; Digital Subscriber Line (DSL) operationaldata; SELT data; throughput data; Wi-Fi performance data; data collectedwhen the user is shopping online using the broadband service; datacollected when the user is browsing the Internet using the broadbandservice; data collected when the user is accessing video online usingthe broadband service; data collected when the user is participating inonline gaming activities using the broadband service; data collectedwhen the user is accessing cloud-based applications using the broadbandservice; data collected when the user is participating in a two-waycommunication using the broadband service; neighborhood configurationdata; or data associated with services and recommendations ofneighboring customers.
 5. The method of claim 1, wherein collecting thedata associated with the broadband service includes collecting back-haulcapacity data associated with the broadband service.
 6. The method ofclaim 1, wherein collecting the data associated with the broadbandservice is initiated by the user via a web-based tool.
 7. The method ofclaim 1, wherein collecting the data includes collecting user preferencedata or usage data associated with the broadband service.
 8. The methodof claim 7, wherein usage data includes at least one of: location of theuser; location of the broadband service associated with the user; Layer3 data; or amount of data packets transmitted and received by the userover a broadband link associated with the broadband service.
 9. Themethod of claim 7, wherein user preference data includes at least oneof: throughput for a broadband link associated with the broadbandservice; stability of line associated with the broadband service; anddelay of the line.
 10. The method of claim 1, wherein evaluating thecollected data comprises: analyzing the collected data to determinewhether a broadband line associated with the broadband service can beupdated to a higher level of service.
 11. The method of claim 1, whereinevaluating the collected data comprises: identifying whether thebroadband service is capable of being upgraded or has to be downgraded.12. The method of claim 11, wherein identifying whether the broadbandservice is capable of being upgraded is performed when it is determinedthat validation records associated with a physical layer indicate thatthe physical layer achieves required data transfer rates.
 13. The methodof claim 11, wherein identifying whether the broadband service iscapable of being upgraded is performed when it is determined thatback-haul capacity is not a limiting factor for service upgrades. 14.The method of claim 1, wherein evaluating the collected data comprisesassigning a score according to at least one of: determination that aphysical layer of the broadband service is stable; determination that abroadband line is stable using a different service product;determination that validation records associated with the physical layerindicate that the physical layer achieves target data transfer rates;and determination that back-haul capacity is not a limiting factor forservice upgrades.
 15. The method of claim 14 further comprises comparingthe score to a threshold.
 16. The method of claim 1, wherein validatingthe broadband service recommendations comprises: prioritizing somebroadband lines for validation relative to a score.
 17. The method ofclaim 16, wherein the score is based on at least one of: availability ofcapacity in backhaul; price of service; quality of customer service;lines, associated with the broadband service, which lack validationrecords; lines, associated with the broadband service, with recentchanges in equipment of service; lines, associated with the broadbandservice, that are more likely to request upgraded service; lines,associated with the broadband service, that are more likely to havehigher up-sell potential; or lines, associated with the broadbandservice, with less accurate service recommendations.
 18. The method ofclaim 1, wherein validating the broadband service recommendationscomprises updating a parameter set associated with the broadbandservice.
 19. The method of claim 18, wherein updating the parameter setis done temporarily.
 20. The method of claim 1 further comprisesperforming profile optimization in response to validating the broadbandservice, wherein profile optimization to adjust one or more parametersin a parameter set associated with the broadband service.
 21. The methodof claim 20, wherein validating the broadband service recommendationscomprises: evaluating the broadband service in response to updating theservice; collecting data associated with the broadband service inresponse to evaluating; checking results associated with the profileoptimization in response to evaluating the broadband service andcollecting the data; and restoring original broadband service to theuser in response to checking results.
 22. The method of claim 1 furthercomprises applying a test profile to a broadband line associated withthe broadband service to determine a type of service the broadband lineis capable of handling.
 23. The method of claim 1 further comprises:presenting the broadband service recommendations to the user of thebroadband service.
 24. A machine readable storage medium havinginstructions stored thereon that, when executed, causes a machine toperform an operation which comprises: collect data associated with thebroadband service; evaluate the collected data for servicerecommendations, the service recommendations including upgrades anddowngrades to the broadband service; and validate broadband servicerecommendations, in response to evaluating the collected data, beforepresenting the broadband service recommendations to user of thebroadband service.
 25. The machine readable storage medium of claim 24,wherein the broadband service is a DSL broadband service.